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US12032994B1 - Linking outputs for automatic execution of tasks - Google Patents

Linking outputs for automatic execution of tasks Download PDF

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Publication number
US12032994B1
US12032994B1 US17/504,450 US202117504450A US12032994B1 US 12032994 B1 US12032994 B1 US 12032994B1 US 202117504450 A US202117504450 A US 202117504450A US 12032994 B1 US12032994 B1 US 12032994B1
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Prior art keywords
task
output
updating
tasks
user
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US17/504,450
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Rebecca Rose Goodwin
Mengxi Chen
Miranda Rose Rensch
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Tableau Software LLC
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Tableau Software LLC
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    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00Arrangements for program control, e.g. control units
    • G06F9/06Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46Multiprogramming arrangements
    • G06F9/48Program initiating; Program switching, e.g. by interrupt
    • G06F9/4806Task transfer initiation or dispatching
    • G06F9/4843Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
    • G06F9/4881Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00Arrangements for program control, e.g. control units
    • G06F9/06Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/44Arrangements for executing specific programs
    • G06F9/451Execution arrangements for user interfaces
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00Error detection; Error correction; Monitoring
    • G06F11/07Responding to the occurrence of a fault, e.g. fault tolerance
    • G06F11/0703Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation
    • G06F11/0751Error or fault detection not based on redundancy
    • G06F11/0754Error or fault detection not based on redundancy by exceeding limits
    • G06F11/076Error or fault detection not based on redundancy by exceeding limits by exceeding a count or rate limit, e.g. word- or bit count limit
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00Error detection; Error correction; Monitoring
    • G06F11/07Responding to the occurrence of a fault, e.g. fault tolerance
    • G06F11/0703Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation
    • G06F11/0766Error or fault reporting or storing
    • G06F11/0772Means for error signaling, e.g. using interrupts, exception flags, dedicated error registers
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00Arrangements for program control, e.g. control units
    • G06F9/06Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46Multiprogramming arrangements
    • G06F9/48Program initiating; Program switching, e.g. by interrupt
    • G06F9/4806Task transfer initiation or dispatching
    • G06F9/4843Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
    • G06F9/485Task life-cycle, e.g. stopping, restarting, resuming execution

Definitions

  • the disclosed implementations relate generally to data visualization and more specifically to systems, methods, and user interfaces to prepare and curate data for processing by a data visualization application.
  • Data visualization applications enable a user to understand a data set visually, including distribution, trends, outliers, and other factors that are important to making business decisions.
  • Some data sets are very large or complex, and include many data fields.
  • Various tools can be used to help understand and analyze the data, including dashboards that have multiple data visualizations.
  • dashboards that have multiple data visualizations.
  • some functionality may be difficult to use or hard to find within a complex user interface.
  • Some implementations provide a new way of linking two or more outputs to be updated according to a predefined schedule. For example, a user can schedule flows to run at a specific time or on a recurring basis to create scheduled tasks that rely on pre-configured schedules.
  • a user is provided with options for selecting which outputs in the flow to automatically update according to the predefined schedule.
  • the system automatically determines tasks that are downstream and/or upstream of a selected task to allow a user to easily link the outputs of one task to initiate execution of another task. By allowing users to link outputs from different tasks together, a user need not worry that upstream data is out-of-date when the task has been linked to the refresh of the upstream data, rather than set to run at a scheduled time. Further, the system can prevent a next task from running when a linked task fails to update, which improves the accuracy of data and enables the system to notify users that created any linked tasks when a task fails.
  • Some implementations provide a method for linking tasks together, such that an update to a first output of a first task automatically triggers execution of a second task.
  • the system automatically provides (e.g., recommends) a list of downstream tasks that can be linked to a particular output.
  • the system is able to take different actions depending on the success or failure of the first output, such that any linked tasks are also flagged (e.g., a notification is sent to the users that linked the tasks), and the subsequent tasks may be paused or stopped in accordance with a failure of the output.
  • a method executes at a computing device (e.g., an electronic device) with a display.
  • the computing device can be a smart phone, a tablet, a notebook computer, or a desktop computer.
  • the method includes receiving a first user input linking a first output of a first task to a second task.
  • the first task is scheduled for execution at a specific time.
  • the method includes, in response to the first user input, providing a list of additional tasks that are downstream from the second task.
  • the method includes receiving a second user input selecting a third task from the list of additional tasks that are downstream from the second task.
  • the method further includes, in response to the second user input, linking the third task to a second output of the second task.
  • the method includes, at the specific time, automatically executing the first task and updating the first output of the first task and after updating the first output of the first task, automatically executing the second task that is linked to the first output of the first task, including updating the second output of the second task.
  • the method further includes, after updating the second output of the second task, automatically executing the third task.
  • a computing device includes one or more processors, memory, a display, and one or more programs stored in the memory.
  • the programs are configured for execution by the one or more processors.
  • the one or more programs include instructions for performing any of the methods described herein.
  • FIG. 1 illustrates a graphical user interface used in some implementations.
  • FIGS. 3 A- 3 S illustrate graphical user interfaces for linking tasks to be executed according to task schedules in accordance with some implementations.
  • FIG. 1 illustrates a graphical user interface 100 for interactive data analysis.
  • the user interface 100 includes a Data tab 114 and an Analytics tab 116 in accordance with some implementations.
  • the Data tab 114 When the Data tab 114 is selected, the user interface 100 displays a schema information region 110 , which is also referred to as a data pane.
  • the schema information region 110 provides named data elements (e.g., field names) that may be selected and used to build a data visualization.
  • the list of field names is separated into a group of dimensions (e.g., categorical data) and a group of measures (e.g., numeric quantities).
  • Some implementations also include a list of parameters.
  • the Analytics tab 116 When the Analytics tab 116 is selected, the user interface displays a list of analytic functions instead of data elements (not shown).
  • the computing device 200 includes a user interface 206 comprising a display device 208 and one or more input devices or mechanisms 210 .
  • the input device/mechanism includes a keyboard.
  • the input device/mechanism includes a “soft” keyboard, which is displayed as needed on the display device 208 , enabling a user to “press keys” that appear on the display 208 .
  • the display 208 and input device/mechanism 210 comprise a touch screen display (also called a touch sensitive display).
  • the memory 214 includes high-speed random access memory, such as DRAM, SRAM, DDR RAM or other random access solid state memory devices.
  • the memory 214 includes non-volatile memory, such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid state storage devices.
  • the memory 214 includes one or more storage devices remotely located from the CPU(s) 202 .
  • the memory 214 or alternatively the non-volatile memory devices within the memory 214 , comprises a non-transitory computer readable storage medium.
  • the memory 214 , or the computer readable storage medium of the memory 214 stores the following programs, modules, and data structures, or a subset thereof:
  • FIG. 3 A illustrates an example user interface 302 - 1 for creating a new scheduled task, “Flow B”.
  • a “flow” e.g., also referred to as a “task” or a “task flow” may be executed to update one or more outputs (“output steps”).
  • output steps For example, a user connects to (e.g., selects) data that is to be included in a flow, and once the data is in the flow, the user can clean and shape the data by adding new steps to the flow or inserting steps in between existing steps.
  • the user can change the default step colors, add descriptions to provide context for the steps or cleaning actions, or reorganize the flow layout to make complex flows easier to follow.
  • flows may be scheduled to run at a specific time and/or on a recurring basis.
  • a user can create scheduled tasks that rely (e.g., execute) on pre-configured schedules.
  • schedules are created by a system administrator.
  • the example user interface 302 - 1 illustrated in FIG. 3 A is a pop-up window (e.g., an overlaid window) displayed over at least a portion of the user interface 100 illustrated in FIG. 1 .
  • the user can create a new task (using the “new task” tab 304 ), including selecting a schedule (using the dropdown 308 ) on which to run the task (e.g., every day at a particular time).
  • the dropdown 308 provides a plurality of options to schedule automatic execution of the task at a particular frequency (e.g., on a particular schedule).
  • the user can specify whether all outputs for the task are to be included (e.g., by selecting the first option 310 “automatically include all outputs of this task”) or whether a subset, less than all, of the output steps should be included in the new task by selecting the second option 312 “select the output steps to include in this task.” If the second option 312 is selected, the user can specify which output steps of the new task are to be updated at the scheduled time. For example, a single task may include a plurality of output steps, as illustrated in the table 314 , which shows the “output steps,” “output name,” “location,” (e.g., identification of a server) and “refresh type”.
  • a scheduled task can include execution (e.g., refresh) of one or more of the output steps of a task. For example a full refresh will refresh all data and create or append data to a table, whereas an incremental refresh will refresh only the new rows and create or append data to a table. The incremental refresh option is only available when the flow is configured in Tableau Prep Builder to use this refresh type.
  • FIG. 3 C illustrates the second user interface 302 - 2 as illustrated in FIG. 3 B , with the schedule dropdown 316 expanded to select a start schedule.
  • the expanded schedule dropdown 316 provides a plurality of flow schedules that have been enabled for linked flow use.
  • administrators have the option to allow (e.g., enable) or block (e.g., disable) the ability for users to link particular flows for particular schedules.
  • only flows that have been enabled (e.g., approved) by an administrator are allowed to be used in linked tasks.
  • the computing device after updating the second output of the second task, performs ( 442 ) a first action based on a result of the second output (e.g., if the second output or second task fails, the system sends an automatic email or sets up a data quality warning on the data source).
  • the system also provides a notification in accordance with a scheduled task successfully running/refreshing. For example, as described with reference to FIG.

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  • Software Systems (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
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  • Human Computer Interaction (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

A computer receives a first user input linking a first output of a first task to a second task. The first task is scheduled for execution at a specific time. The computer receives a second user input selecting a third task from a list of additional tasks that are downstream from the second task. In response to the second user input, the computer links the third task to a second output of the second task. At the specific time, the computer automatically executes the first task and updates the first output of the first task. After updating the first output of the first task, the computer automatically executes the second task that is linked to the first output of the first task, including updating the second output of the second task. After updating the second output of the second task, the computer automatically executes the third task.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS
The present application is related to the following five applications, each of which is incorporated by reference herein in its entirety:
    • U.S. patent application Ser. No. 15/701,381, filed Sep. 11, 2017, entitled “Optimizing Execution of Data Transformation Flows,” now U.S. Pat. No. 10,242,079;
    • U.S. patent application Ser. No. 15/345,391, filed Nov. 7, 2016, entitled “User Interface to Prepare and Curate Data for Subsequent Analysis;”
    • U.S. patent application Ser. No. 16/155,818, filed Oct. 9, 2018, entitled “Correlated Incremental Loading of Multiple Data Sets for an Interactive Data Prep Application,” now U.S. Pat. No. 10,885,057;
    • U.S. patent application Ser. No. 16/167,313, filed Oct. 22, 2018, entitled “Data Preparation User Interface with Conglomerate Heterogeneous Process Flow Elements,” now U.S. Pat. No. 10,691,304; and
    • U.S. patent application Ser. No. 16/228,680, filed Dec. 20, 2018, entitled “Data Preparation User Interface with Conditional Remapping of Data Values.”
TECHNICAL FIELD
The disclosed implementations relate generally to data visualization and more specifically to systems, methods, and user interfaces to prepare and curate data for processing by a data visualization application.
BACKGROUND
Data visualization applications enable a user to understand a data set visually, including distribution, trends, outliers, and other factors that are important to making business decisions. Some data sets are very large or complex, and include many data fields. Various tools can be used to help understand and analyze the data, including dashboards that have multiple data visualizations. However, some functionality may be difficult to use or hard to find within a complex user interface. In addition, when a dashboard has multiple related data visualizations, it is not apparent how changes to one visualization would affect the other visualizations.
SUMMARY
Some implementations provide a new way of linking two or more outputs to be updated according to a predefined schedule. For example, a user can schedule flows to run at a specific time or on a recurring basis to create scheduled tasks that rely on pre-configured schedules. In addition, a user is provided with options for selecting which outputs in the flow to automatically update according to the predefined schedule. The system automatically determines tasks that are downstream and/or upstream of a selected task to allow a user to easily link the outputs of one task to initiate execution of another task. By allowing users to link outputs from different tasks together, a user need not worry that upstream data is out-of-date when the task has been linked to the refresh of the upstream data, rather than set to run at a scheduled time. Further, the system can prevent a next task from running when a linked task fails to update, which improves the accuracy of data and enables the system to notify users that created any linked tasks when a task fails.
Some implementations provide a method for linking tasks together, such that an update to a first output of a first task automatically triggers execution of a second task. The system automatically provides (e.g., recommends) a list of downstream tasks that can be linked to a particular output. In addition, the system is able to take different actions depending on the success or failure of the first output, such that any linked tasks are also flagged (e.g., a notification is sent to the users that linked the tasks), and the subsequent tasks may be paused or stopped in accordance with a failure of the output. To that end, in accordance with some implementations, a method executes at a computing device (e.g., an electronic device) with a display. For example, the computing device can be a smart phone, a tablet, a notebook computer, or a desktop computer. The method includes receiving a first user input linking a first output of a first task to a second task. The first task is scheduled for execution at a specific time. The method includes, in response to the first user input, providing a list of additional tasks that are downstream from the second task. The method includes receiving a second user input selecting a third task from the list of additional tasks that are downstream from the second task. The method further includes, in response to the second user input, linking the third task to a second output of the second task. The method includes, at the specific time, automatically executing the first task and updating the first output of the first task and after updating the first output of the first task, automatically executing the second task that is linked to the first output of the first task, including updating the second output of the second task. The method further includes, after updating the second output of the second task, automatically executing the third task.
In some implementations, a computing device includes one or more processors, memory, a display, and one or more programs stored in the memory. The programs are configured for execution by the one or more processors. The one or more programs include instructions for performing any of the methods described herein.
In some implementations, a non-transitory computer readable storage medium stores one or more programs configured for execution by a computing device having one or more processors, memory, and a display. The one or more programs include instructions for performing any of the methods described herein.
Thus methods, systems, and graphical user interfaces are disclosed that enable users to easily interact with multiple related data visualizations and data prep flows.
BRIEF DESCRIPTION OF THE DRAWINGS
For a better understanding of the aforementioned systems, methods, and graphical user interfaces, as well as additional systems, methods, and graphical user interfaces that provide data visualization analytics, reference should be made to the Description of Implementations below, in conjunction with the following drawings in which like reference numerals refer to corresponding parts throughout the figures.
FIG. 1 illustrates a graphical user interface used in some implementations.
FIG. 2 is a block diagram of a computing device according to some implementations.
FIGS. 3A-3S illustrate graphical user interfaces for linking tasks to be executed according to task schedules in accordance with some implementations.
FIGS. 4A and 4B provide a flowchart of a process for linking tasks for automatic execution according to some implementations.
Reference will now be made to implementations, examples of which are illustrated in the accompanying drawings. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. However, it will be apparent to one of ordinary skill in the art that the present invention may be practiced without requiring these specific details.
DESCRIPTION OF IMPLEMENTATIONS
FIG. 1 illustrates a graphical user interface 100 for interactive data analysis. The user interface 100 includes a Data tab 114 and an Analytics tab 116 in accordance with some implementations. When the Data tab 114 is selected, the user interface 100 displays a schema information region 110, which is also referred to as a data pane. The schema information region 110 provides named data elements (e.g., field names) that may be selected and used to build a data visualization. In some implementations, the list of field names is separated into a group of dimensions (e.g., categorical data) and a group of measures (e.g., numeric quantities). Some implementations also include a list of parameters. When the Analytics tab 116 is selected, the user interface displays a list of analytic functions instead of data elements (not shown).
The graphical user interface 100 also includes a data visualization region 112. The data visualization region 112 includes a plurality of shelf regions, such as a columns shelf region 120 and a rows shelf region 122. These are also referred to as the column shelf 120 and the row shelf 122. As illustrated here, the data visualization region 112 also has a large space for displaying a visual graphic. Because no data elements have been selected yet, the space initially has no visual graphic. In some implementations, the data visualization region 112 has multiple layers that are referred to as sheets.
FIG. 2 is a block diagram illustrating a computing device 200 that can display the graphical user interface 100 in accordance with some implementations. The computing device can also be used by a data preparation (“data prep”) application 250. Various examples of the computing device 200 include a desktop computer, a laptop computer, a tablet computer, and other computing devices that have a display and a processor capable of running a data visualization application 222. The computing device 200 typically includes one or more processing units/cores (CPUs) 202 for executing modules, programs, and/or instructions stored in the memory 214 and thereby performing processing operations; one or more network or other communications interfaces 204; memory 214; and one or more communication buses 212 for interconnecting these components. The communication buses 212 may include circuitry that interconnects and controls communications between system components.
The computing device 200 includes a user interface 206 comprising a display device 208 and one or more input devices or mechanisms 210. In some implementations, the input device/mechanism includes a keyboard. In some implementations, the input device/mechanism includes a “soft” keyboard, which is displayed as needed on the display device 208, enabling a user to “press keys” that appear on the display 208. In some implementations, the display 208 and input device/mechanism 210 comprise a touch screen display (also called a touch sensitive display).
In some implementations, the memory 214 includes high-speed random access memory, such as DRAM, SRAM, DDR RAM or other random access solid state memory devices. In some implementations, the memory 214 includes non-volatile memory, such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid state storage devices. In some implementations, the memory 214 includes one or more storage devices remotely located from the CPU(s) 202. The memory 214, or alternatively the non-volatile memory devices within the memory 214, comprises a non-transitory computer readable storage medium. In some implementations, the memory 214, or the computer readable storage medium of the memory 214, stores the following programs, modules, and data structures, or a subset thereof:
    • an operating system 216, which includes procedures for handling various basic system services and for performing hardware dependent tasks;
    • a communications module 218, which is used for connecting the computing device 200 to other computers and devices via the one or more communication network interfaces 204 (wired or wireless) and one or more communication networks, such as the Internet, other wide area networks, local area networks, metropolitan area networks, and so on;
    • a web browser 220 (or other application capable of displaying web pages), which enables a user to communicate over a network with remote computers or devices;
    • a data visualization application 222, which provides a graphical user interface 100 for a user to construct visual graphics. For example, a user selects one or more data sources 240 (which may be stored on the computing device 200 or stored remotely), selects data fields from the data sources, and uses the selected fields to define a visual graphic. In some implementations, the information the user provides is stored as a visual specification 228. The data visualization application 222 includes a data visualization generation module 226, which takes the user input (e.g., the visual specification 228), and generates a corresponding visual graphic (also referred to as a “data visualization” or a “data viz”). The data visualization application 222 then displays the generated visual graphic in the user interface 100. In some implementations, the data visualization application 222 executes as a standalone application (e.g., a desktop application). In some implementations, the data visualization application 222 executes within the web browser 220 or another application using web pages provided by a web server; and
    • zero or more databases or data sources 240 (e.g., a first data source 240-1 and a second data source 240-2), which are used by the data visualization application 222. In some implementations, the data sources are stored as spreadsheet files, CSV files, XML files, or flat files, or stored in a relational database.
Each of the above identified executable modules, applications, or sets of procedures may be stored in one or more of the previously mentioned memory devices, and corresponds to a set of instructions for performing a function described above. The above identified modules or programs (i.e., sets of instructions) need not be implemented as separate software programs, procedures, or modules, and thus various subsets of these modules may be combined or otherwise re-arranged in various implementations. In some implementations, the memory 214 stores a subset of the modules and data structures identified above. Furthermore, the memory 214 may store additional modules or data structures not described above.
Although FIG. 2 shows a computing device 200, FIG. 2 is intended more as a functional description of the various features that may be present rather than as a structural schematic of the implementations described herein. In practice, and as recognized by those of ordinary skill in the art, items shown separately could be combined and some items could be separated.
FIG. 3A illustrates an example user interface 302-1 for creating a new scheduled task, “Flow B”. As used herein, a “flow” (e.g., also referred to as a “task” or a “task flow”) may be executed to update one or more outputs (“output steps”). For example, a user connects to (e.g., selects) data that is to be included in a flow, and once the data is in the flow, the user can clean and shape the data by adding new steps to the flow or inserting steps in between existing steps. In some implementations, to organize the flow, the user can change the default step colors, add descriptions to provide context for the steps or cleaning actions, or reorganize the flow layout to make complex flows easier to follow. In some implementations, flows may be scheduled to run at a specific time and/or on a recurring basis. For example, a user can create scheduled tasks that rely (e.g., execute) on pre-configured schedules. In some implementations, schedules are created by a system administrator.
In some implementations, the example user interface 302-1 illustrated in FIG. 3A is a pop-up window (e.g., an overlaid window) displayed over at least a portion of the user interface 100 illustrated in FIG. 1 . For example, the user can create a new task (using the “new task” tab 304), including selecting a schedule (using the dropdown 308) on which to run the task (e.g., every day at a particular time). For example, the dropdown 308 provides a plurality of options to schedule automatic execution of the task at a particular frequency (e.g., on a particular schedule).
In some implementations, the user can specify whether all outputs for the task are to be included (e.g., by selecting the first option 310 “automatically include all outputs of this task”) or whether a subset, less than all, of the output steps should be included in the new task by selecting the second option 312 “select the output steps to include in this task.” If the second option 312 is selected, the user can specify which output steps of the new task are to be updated at the scheduled time. For example, a single task may include a plurality of output steps, as illustrated in the table 314, which shows the “output steps,” “output name,” “location,” (e.g., identification of a server) and “refresh type”. In some implementations, a scheduled task can include execution (e.g., refresh) of one or more of the output steps of a task. For example a full refresh will refresh all data and create or append data to a table, whereas an incremental refresh will refresh only the new rows and create or append data to a table. The incremental refresh option is only available when the flow is configured in Tableau Prep Builder to use this refresh type.
FIG. 3B illustrates a second user interface 302-2, which is the example user interface shown in FIG. 3A, but with the “linked tasks” tab 306 selected. This enables the user to add a task to be linked to run after the task (e.g., the new task created in FIG. 3A). For example, when the linked tasks tab 306 is selected, the user can select a start schedule using the schedule dropdown 316. In this example, the first task selected (with a numeric indicator 318 “1” indicating that it is the first task) is Flow B. For Flow B, the user can select, using the outputs dropdown 320, which outputs to include in the execution of Flow B (e.g., all flow outputs (3)—Full Refresh). This matches the selections made when creating Flow B in FIG. 3A. The user interface further includes an indication of what actions will occur based on the success or failure of executing Flow B. For example, if the task “Flow B” succeeds, a next task (e.g., which will be selected below using the next task dropdown 326) will start, and if “Flow B” fails, the next tasks (e.g., remaining tasks) will not be executed and a notification (e.g., an email) will be sent to the user (e.g., the creator of the linked tasks). In some implementations, the user may also select (e.g., by selecting the data quality option 321) to add a data quality warning (e.g., to indicate in later tasks that certain outputs have not been successfully updated and therefore the data may not be up-to-date) if the task fails. The user interface further provides a Delete option 322 to delete the task.
A second numerical indicator 324 (“2”) indicates a second flow that is to be executed after the first flow indicated by “1”. For example, the flows are numbered according to the order in which they execute in the schedule. The user can select a flow to execute after Flow B has completed (e.g., successfully) using the next task dropdown 326. The user can add additional tasks (e.g., 3, 4, etc.) using the Add button 328 (“Add next task”).
FIG. 3C illustrates the second user interface 302-2 as illustrated in FIG. 3B, with the schedule dropdown 316 expanded to select a start schedule. For example, the expanded schedule dropdown 316 provides a plurality of flow schedules that have been enabled for linked flow use. For example, administrators have the option to allow (e.g., enable) or block (e.g., disable) the ability for users to link particular flows for particular schedules. For example, only flows that have been enabled (e.g., approved) by an administrator are allowed to be used in linked tasks. The available schedules provided in the expanded schedule dropdown 316 include a plurality of periodic scheduling options, such as “End of the month”, “hourly”, “Monday morning”, “every night at 11:00 PM”, “Every Sunday—9:00 AM.” In some implementations, each of the schedules presented as an option in the schedule dropdown 316 correspond to a scheduled task for which an administrator has enabled linked tasks. In some implementations, only administrators are enabled to “Add a Schedule.” An administrator can create a new flow schedule or release additional scheduling options for non-administrator users.
FIG. 3D illustrates expansion of the next task dropdown 326 to provide options for a next flow to be linked from “Flow B.” For example, a user can select individual downstream flows by clicking a row or opening the flow in a new tab (e.g., by clicking the link), or can select multiple flows using the check boxes.
FIG. 3E illustrates alternative options presented in response to expanding the next task dropdown 326. For example, the user interface displays a message indicating that no downstream flows are found (e.g., because all downstream flows are unavailable or there are no downstream flows). In some implementations, the user interface provides a search option (e.g., a search bar 328) such that the user may search for a particular flow to add. In some implementations, the user interface displays a link 330 to view all flows.
FIG. 3F illustrates the user interface providing an option (e.g., using the flow dropdown 331) to add a flow to be executed before Flow B (e.g., add an upstream flow to Flow B). In this example, the upstream flow is assigned the numeric indicator “1” 318 and Flow B is moved to a position with the numeric indicator “2” because Flow B is downstream from Flow A (and will therefore be executed after Flow A). In this example, a plurality of flows that are upstream from Flow B are displayed with selectable boxes, including a first selectable box 332 (e.g., a check box) for Flow A and a second selectable box 334 (e.g., check box) for Flow Alpha. However, Flow Alpha (e.g., the selectable box and description for Flow Alpha) is displayed as greyed out (or otherwise is presented as not selectable). As illustrated in FIG. 3F, a tooltip 336 (e.g., which is displayed in response to a user input, such as hovering over an information icon) explains why Flow Alpha is not selectable. Tooltip 336 recites “To run this flow you must have permission from the flow owner and the flow must be assigned to a schedule that is enabled for linked tasks.” For example, if there is an upstream (e.g., or downstream) flow, but the user does not have permission to schedule the flow (e.g., “Flow Alpha”), the flow appears as disabled (e.g., greyed out) in the list of upstream or downstream flows.
FIG. 3G illustrates the user reordering the scheduled flows (e.g., tasks). For example, Flow B is initially in position 1 (e.g., as indicated by the first numeric indicator 318), to be executed before Flow C (e.g., in position 2). The device receives a user input (e.g., on the numeric indicator “2”), and in response to the user input, the device provides a set of options 338 for the user to reorder the flows: for example, to move Flow C “up one”, “down one”, “to beginning”, or “to end.” In addition, the user is presented with options to add new tasks before and/or after Flow C. In some implementations, the user can select the numerical indicator and drag the flow to a different position within the list of flows to re-order the flows. In some implementations, the “move icon” appears in response to detecting a hover input and while the tasks are being re-ordered. In some implementations, this also provides a way for the user to add a task above or below an existing task.
FIG. 3H illustrates a detailed view of configuring the data quality warning option 321 (e.g., as described above with reference to FIG. 3B). In some implementations, in response to the user selecting to add a data quality warning (e.g., by selecting the check box option 321), the user is presented with a plurality of options for the quality warning. For example, the user is provided with a second option 325 to show a “high visibility” warning (e.g., to notify when users open a published view that is affected by the data quality warning). The user is also provided with a message option 327 to add a message to be displayed with the data quality warning (e.g., a more detailed explanation of the warning). In some implementations, the “flow run monitoring” option 323 is automatically selected (e.g., the check box is filled) in accordance with the “add data quality warning” check box being selected. Note that data quality rules are specified elsewhere. The interface here determines what warnings are provided based on flow execution.
FIG. 3I illustrates a user interface 350 for viewing scheduled tasks. For example, FIG. 3I illustrates that there are 2 scheduled tasks. In addition, the interface 350 includes an option 352 to add a new task. For example, a first scheduled task is scheduled to run every night at 11:00 PM. The user interface 350 further includes a status of the scheduled tasks (e.g., indicating if the task failed or succeeded). For example, the status indicator 354 illustrates that the first scheduled task has “Failed” and displays a next scheduled time that the task will run. The user interface includes details about the first scheduled task, such as details about the output steps for the task (e.g., the output name, the type, the location, and the refresh type). In some implementations, when a scheduled task fails, the computing device sends a notification to users who linked any other tasks to the failed scheduled task. In some implementations, when a task fails a predefined number of times, the tasks linked to run after the failing task are suspended (e.g., not executed), to prevent stale data from propagating through the linked tasks until a user is able to fix the failed scheduled task.
FIG. 3J illustrates an alternative version of the user interface in FIG. 3I. The alternative version displays additional details about the linked tasks. For example, FIG. 3J illustrates a user interface for viewing scheduled tasks in a table view because, after linking a plurality of tasks together (e.g., for scheduled execution of one task after another), additional tasks are displayed in the view (e.g., to allow users to also view downstream linked tasks that use the current flow to run). In some implementations, the table view illustrated in FIG. 3J for displaying scheduled tasks is more scalable and better for sorting and/or filtering than the user interface illustrated in FIG. 3I. Further, the user interface in FIG. 3J includes a column that indicates the scheduled task type and where the flow occurs within the linked task (e.g., 1/2 linked tasks). For example, the clickable elements (e.g., links), when selected, show flow outputs and linked tasks. In some implementations, the same functionality is provided in the user interface illustrated in FIG. 3I (plus additional functionality). FIG. 3J further illustrates that the user can select the “number of outputs” link to see the selected output details and refresh types. For example, the user can select to view more details in order to see a separate output dialog box 356. The output dialog box includes additional information for the selected outputs (e.g., in response to a user hovering over “Farmers and County+2”). Additional details regarding the additional (e.g., +2) outputs are shown in box 356.
In some implementations, the user interface further provides a sort option 358 to sort the list of tasks. For example, a user can sort by name (e.g., A to Z), or otherwise filter the tasks that are shown (e.g., filter by task type and/or the user who created the schedule). For example, a user can choose to view only schedules that were created by the user.
FIG. 3K illustrates a user interface displayed for an administrator (e.g., in a settings user interface for the administrator) to control whether other users are enabled to link tasks together for particular sites. For example, an administrator controls which of the sites will allow other users to use the linked tasks functionality using the options presented in the Linked Tasks dialog box 360.
FIG. 3L illustrates a user interface for viewing schedules, which is displayed for an administrator. For example, the list of schedules enables the administrator to view for which schedules linked tasks are allowed or unavailable. For example, the administrator is provided with the Name 361 for each scheduled task, the frequency 362 for each scheduled task, the task type 363 (e.g., an extract refresh, a flow, or a subscription), the number of tasks 364 that are scheduled (e.g., optionally including linked tasks), an indication 365 of whether the linked tasks are enabled for the scheduled task, and an indication 366 of a next time at which the scheduled task is going to run. In some implementations, each task listed in the schedule has zero or more tasks (e.g., flows) that are executed at the scheduled frequency. For example, one or more of the scheduled tasks illustrated in FIG. 3L are not “linked” to other tasks (e.g., each of the scheduled tasks includes zero or more “normal” tasks for the schedule that is not linked to any other tasks). Note that the interface mock-up includes developer annotations that are not displayed in live versions of the interface.
FIG. 3M illustrates a user interface for creating a new schedule. In some implementations, the user interface provides a first selectable option 369-1 (e.g., and the second selectable option 369-2) for enabling linked tasks for the schedule. In some implementations, only tasks that are scheduled for parallel execution (e.g., as indicated by the first execution dropdown 368-1) are enabled to be linked, whereas tasks scheduled for serial execution (e.g., as indicated by the second execution dropdown 368-2) are not enabled to be linked (and the “linked tasks” option 369-2 is greyed out).
FIG. 3N illustrates an example of viewing tasks that are scheduled for a particular time (e.g., the end of the month). In some implementations, the view includes displaying one or more flows 370 (e.g., tasks), including a number of tasks that are linked to each flow and their output steps 371. In some implementations, the user interface further displays an indication of priority 372 and a status of the tasks 373 (e.g., whether each task succeeded or failed). In some implementations, the computing device displays additional details as to why a task failed (e.g., in response to a user input selecting the “failed” status, such as a hover input over the failed status indicator). For example, the computing device displays a message that states a flow is missing or cannot be found, and instructs the user to edit the task in order to continue running the schedule (e.g., after the failed task is edited and can run).
FIG. 3O illustrates a schedule indicating that flow A 374, flow B 375, flow C 376, and flow D 377 will run in the recited order. FIG. 3O further illustrates a plurality of output steps for flow B 375 (e.g., task B). For example, each flow (e.g., task) includes a plurality of output steps and another task may be linked from any of the output steps. A linked task does not have to wait for another task to complete entirely; instead, another task can be linked to one of the outputs of the task, such that once the designated output is updated, the linked task runs.
FIG. 3P illustrates a user interface for modifying the scheduled linked flows shown in FIG. 3O. In some implementations, if similar linked tasks or scheduled tasks are detected, the device provides a warning 378 to the user. For example, in this case, if an existing linked task already runs flow A.1 on Mondays at 2 μm and then runs Flow B, the warning 378 indicates this existing link between flow A.1 and Flow B, even though the current linked task links Flow B to run after A.3 (which will already automatically run after flows A.1 and A.2). Accordingly, the computing device determines whether similar linked tasks or scheduled tasks already exist for flows and automatically presents a warning indication to the user if the user is trying to create a different linked relationship between the tasks (or delete a task that is linked to another task).
FIG. 3Q illustrates the edit mode in which the computing device warns a user (e.g., with the warning message 380) that a flow (e.g., task) no longer exists (e.g., the flow is missing or cannot be found). For example, the computing device prompts the user to delete or replace the flow. For example, the flow selection dropdown 381 provides a list of available flows that have been identified by the computing device as being downstream of Flow A and/or Flow B.10 for the user to select an available downstream flow.
FIG. 3R illustrates an example user interface that displays a plurality of upstream flows (e.g., relative to Flow B) that may be selected to execute before Flow B, thereby linking an output of the upstream flow to Flow B. For example, the computing device automatically identifies zero or more upstream flows of Flow B and displays the identified flows (e.g., Flow A and Flow Alpha). In some implementations, one or more of the identified upstream flows are not selectable (e.g., Flow Alpha is greyed out and not selectable) in accordance with the flow not being available for linked tasks (e.g., an administrator has not enabled linked tasks for Flow Alpha). In some implementations, the computing device automatically (e.g., without user input) determines whether the user has permission to refresh (e.g., update) the upstream (and/or downstream) flows. For example, the user does not have permission to refresh Flow A, but the user can use one of the existing schedules for Flow A to start the linked tasks (e.g., Flow B can run after Flow A is updated). In this way, a user is not able to access or refresh flows for which the user does not have permission, but the user is still enabled to use an output (e.g., one that is refreshed according to an existing schedule) to initiate execution of Flow B. Note that at least one of the upstream schedules for Flow A must have linked tasks enabled (e.g., by an administrator) for the user to link an output of Flow A to Flow B.
FIG. 3S illustrates an error message that is displayed when the user not yet selecting a scheduled task to initiate flows A and B according to the schedule. For example, different options (e.g., selecting the output and full versus incremental updates) are provided to the user based on the schedule. For example, as illustrated in FIG. 3O, for a selected flow (e.g., Flow B), a plurality of output steps may be selected. Each output step also has a refresh type (e.g., a full refresh or an incremental refresh).
Some of the screens illustrated in FIGS. 3A-3S include developer annotations, which are not displayed in live versions. The developer annotations are rectangular boxes with horizontal triangular protrusions. For example, FIG. 3S includes two developer annotations.
FIGS. 4A and 4B provide a flowchart of a process 410 for linking (412) tasks for automatic execution according to some implementations. The process is performed (414) at a computing device (e.g., a computer) having a display, one or more processors, and memory. The memory stores (416) one or more programs (e.g., a data prep application 250) configured for execution by the one or more processors.
The computing device receives (418) a first user input linking a first output of a first task to a second task. The first task is scheduled for execution at a specific time. In some instances, the second task is downstream from the first task.
In some implementations, the computing device determines (420) whether the first task is upstream of the second task (e.g., where tasks are ordered in a data catalog from upstream to downstream).
In some implementations, the specific time is determined (422) based on the occurrence of a predefined event. For example, the predefined event occurs when all upstream jobs complete, when one or more applications finish refreshing, when one or more extraction flows complete, and/or when (in response to) new data arrives. In some implementations, the predefined event occurs according to a schedule (e.g., every day at a particular time).
In response to the first user input, the computing device provides (424) (e.g., automatically populates) a list of additional tasks that are downstream from the second task. For example, as illustrated in FIG. 3Q, the computing device provides a dropdown 381 that includes a list of downstream flows that are available to be linked to the second task.
The computing device receives (426) a second user input selecting a third task from the list of additional tasks that are downstream from the second task.
In some implementations, prior to linking the third task to the second output of the second task, the computing device determines (430) that the user has permission to execute the third task. In some implementations, the computing device determines that the user has permission to execute the first task before linking the first task to the second task. For example, users that do not have permission to execute a task cannot link the task to other tasks. In some implementations, the computing device checks permissions to run all of the tasks that are linked together, and when there is an error (e.g., due to the user not having permission to run all of the tasks), the computing device displays an indication of the error. In some implementations, the computing device also provides a data quality warning to indicate there has been a data error. In some implementations, data quality errors occur when a data value for a data field fails to satisfy one or more user-defined rules. For example, a rule may specify that a data field has non-NULL values, specify that data values for a numeric data field fall within a designated range (e.g., 2020-2030), or specify a set of discrete allowed data values for a dimension data field.
In response to the second user input, the computing device links (432) the third task to a second output of the second task. The third task can be scheduled to execute when the second output is available, even if the second task has multiple outputs, which are not all complete. The third task does not have to wait for complete execution of the second task (e.g., for all outputs of the second task to be updated). Instead, the third task is linked to an output of the second task such that, in response to completion of the second output of the second task, the third task begins to execute.
At the specific time (e.g., selected based on a schedule, as described with reference to FIG. 3C), the computing device automatically executes (434) the first task and updates the first output of the first task.
In some implementations, executing the first task comprises (436) updating only a first output without updating an additional output of the first task before automatically executing the second task that is linked to the first output of the first task.
After updating the first output of the first task, the computing device automatically executes (438) the second task that is linked to the first output of the first task.
In some instances, after updating the second output of the second task, the computing device publishes (440) a result of the first output of the first task and a result of the second output of the second task to a public board. In some instances, the first output of the first task is published after the first task has completed execution (e.g., without waiting for the second task to also execute/complete). In some instances, the first output of the first task is linked to the second task such that the output of the first task is not published until the second task has also completed.
In some implementations, after updating the second output of the second task, the computing device performs (442) a first action based on a result of the second output (e.g., if the second output or second task fails, the system sends an automatic email or sets up a data quality warning on the data source). In some implementations, the system also provides a notification in accordance with a scheduled task successfully running/refreshing. For example, as described with reference to FIG. 3B, the user can select an option such that if the task “Flow B” succeeds, a next task (e.g., which will be selected below using dropdown 326) will start, and if “Flow B” fails, the next tasks (e.g., the remaining tasks) will not be executed and a notification (e.g., an email) will be sent to the user (e.g., the creator of the linked tasks).
After updating the second output of the second task, the computing device automatically executes (444) the third task. In this way, the first task (e.g., a scheduled task) that updates a first output causes the tasks linked to the first output to also be executed. For example, instead of adding the linked tasks to the schedule directly, the linked tasks can depend on an output of a scheduled task without requiring the user to create a new schedule to execute the linked task.
In some implementations, when execution of the second task fails a predefined number of times, the computing device automatically suspends (446) execution of the second task and the third task and any other tasks linked to the second task, including blocking all of the following (downstream) flows. In some implementations, the user can decide whether or not to allow the remaining tasks to continue running if a task fails, as described with reference to FIG. 3B. For example, the computing device blocks the third task after the second task fails. In some implementations, the computing device pauses and/or removes any remaining tasks in the linked flows.
The disclosed implementations typically provide “instant” or “real-time” updates or feedback based on user actions. In practice, “instant” or “real-time” means within a short period of time and without additional user input. For example, the “instant” or “real-time” updates may occur within one twentieth of a second, one tenth of a second, one half of a second, or a second. As computer processors become more powerful, instant updates can occur more quickly and/or for even more complex operations.
The terminology used in the description of the invention herein is for the purpose of describing particular implementations only and is not intended to be limiting of the invention. As used in the description of the invention and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that the term “and/or” as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items. It will be further understood that the terms “comprises” and/or “comprising,” when used in this specification, specify the presence of stated features, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, elements, components, and/or groups thereof.
The foregoing description, for purpose of explanation, has been described with reference to specific implementations. However, the illustrative discussions above are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Many modifications and variations are possible in view of the above teachings. The implementations were chosen and described in order to best explain the principles of the invention and its practical applications, to thereby enable others skilled in the art to best utilize the invention and various implementations with various modifications as are suited to the particular use contemplated.

Claims (20)

What is claimed is:
1. A method for linking tasks, comprising:
at a computing device having a display, one or more processors, and memory storing one or more programs configured for execution by the one or more processors:
receiving a first user input linking a first output of a first task to a second task, wherein the first task is scheduled for execution at a specific time;
in response to the first user input, providing a list of additional tasks that are downstream from the second task;
receiving a second user input selecting a third task from the list of additional tasks that are downstream from the second task;
in response to the second user input, linking the third task to a second output of the second task; and
at the specific time:
automatically executing the first task and updating the first output of the first task without updating an additional output of the first task before automatically executing the second task that is linked to the first output of the first task;
after updating the first output of the first task, automatically executing the second task that is linked to the first output of the first task, including updating the second output of the second task; and
after updating the second output of the second task, automatically executing the third task.
2. The method of claim 1, further comprising, determining whether the first task is upstream of the second task.
3. The method of claim 1, further comprising, after updating the second output of the second task, publishing a result of the first output of the first task and a result of the second output of the second task to a public board.
4. The method of claim 1, wherein the specific time is determined based on the occurrence of a predefined event.
5. The method of claim 1, further comprising, prior to linking the third task to the second output of the second task, determining that the user has permission to execute the third task.
6. The method of claim 1, further comprising, after updating the second output of the second task, performing a first action based on a result of the second output.
7. The method of claim 1, further comprising, in accordance with a determination that execution of the second task fails a predefined number of times, automatically suspending execution of the second task and the third task.
8. A computing device, comprising:
one or more processors;
memory;
a display; and
one or more programs stored in the memory and configured for execution by the one or more processors, the one or more programs comprising instructions for:
receiving a first user input linking a first output of a first task to a second task, wherein the first task is scheduled for execution at a specific time;
in response to the first user input, providing a list of additional tasks that are downstream from the second task;
receiving a second user input selecting a third task from the list of additional tasks that are downstream from the second task;
in response to the second user input, linking the third task to a second output of the second task; and
at the specific time:
automatically executing the first task and updating the first output of the first task without updating an additional output of the first task before automatically executing the second task that is linked to the first output of the first task;
after updating the first output of the first task, automatically executing the second task that is linked to the first output of the first task, including updating the second output of the second task; and
after updating the second output of the second task, automatically executing the third task.
9. The computing device of claim 8, wherein the one or more programs further comprise instructions for determining whether the first task is upstream of the second task.
10. The computing device of claim 8, wherein the one or more programs further comprise instructions for, after updating the second output of the second task, publishing a result of the first output of the first task and a result of the second output of the second task to a public board.
11. The computing device of claim 8, wherein the specific time is determined based on the occurrence of a predefined event.
12. The computing device of claim 8, wherein the one or more programs further comprise instructions for, prior to linking the third task to the second output of the second task, determining that the user has permission to execute the third task.
13. The computing device of claim 8, wherein the one or more programs further comprise instructions for, after updating the second output of the second task, performing a first action based on a result of the second output.
14. The computing device of claim 8, wherein the one or more programs further comprise instructions for, in accordance with a determination that execution of the second task fails a predefined number of times, automatically suspending execution of the second task and the third task.
15. A non-transitory computer readable storage medium storing one or more programs configured for execution by a computing device having one or more processors, memory, and a display, the one or more programs comprising instructions for:
receiving a first user input linking a first output of a first task to a second task, wherein the first task is scheduled for execution at a specific time;
in response to the first user input, providing a list of additional tasks that are downstream from the second task;
receiving a second user input selecting a third task from the list of additional tasks that are downstream from the second task;
in response to the second user input, linking the third task to a second output of the second task; and
at the specific time:
automatically executing the first task and updating the first output of the first task without updating an additional output of the first task before automatically executing the second task that is linked to the first output of the first task;
after updating the first output of the first task, automatically executing the second task that is linked to the first output of the first task, including updating the second output of the second task; and
after updating the second output of the second task, automatically executing the third task.
16. The computer readable storage medium of claim 15, wherein the one or more programs further comprise instructions for determining whether the first task is upstream of the second task.
17. The computer readable storage medium of claim 15, wherein the one or more programs further comprise instructions for, after updating the second output of the second task, publishing a result of the first output of the first task and a result of the second output of the second task to a public board.
18. The computer readable storage medium of claim 15, wherein the specific time is determined based on the occurrence of a predefined event.
19. The computer readable storage medium of claim 15, wherein the one or more programs further comprise instructions for, prior to linking the third task to the second output of the second task, determining that the user has permission to execute the third task.
20. The computer readable storage medium of claim 15, wherein the one or more programs further comprise instructions for, after updating the second output of the second task, performing a first action based on a result of the second output.
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Citations (160)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4357673A (en) 1980-04-18 1982-11-02 Hewlett-Packard Company Apparatus for performing measurements and error analysis of the measurements
US4458323A (en) 1980-04-18 1984-07-03 Hewlett-Packard Company Method of performing measurements and error analysis of the measurements
US5339392A (en) 1989-07-27 1994-08-16 Risberg Jeffrey S Apparatus and method for creation of a user definable video displayed document showing changes in real time data
US5421008A (en) 1991-11-08 1995-05-30 International Business Machines Corporation System for interactive graphical construction of a data base query and storing of the query object links as an object
US5999192A (en) 1996-04-30 1999-12-07 Lucent Technologies Inc. Interactive data exploration apparatus and methods
US6278452B1 (en) 1998-09-18 2001-08-21 Oracle Corporation Concise dynamic user interface for comparing hierarchically structured collections of objects
US20020055947A1 (en) 1997-08-18 2002-05-09 National Instruments Corporation System and method for deploying a graphical program on an image acquisition device
US20020070953A1 (en) 2000-05-04 2002-06-13 Barg Timothy A. Systems and methods for visualizing and analyzing conditioned data
US20020080174A1 (en) 1997-08-18 2002-06-27 National Instruments Corporation System and method for configuring an instrument to perform measurement functions utilizing conversion of graphical programs into hardware implementations
US6470344B1 (en) 1999-05-29 2002-10-22 Oracle Corporation Buffering a hierarchical index of multi-dimensional data
US20020157086A1 (en) 1999-02-04 2002-10-24 Lewis Brad R. Methods and systems for developing data flow programs
US20030088546A1 (en) 2001-10-12 2003-05-08 Brown Douglas P. Collecting and/or presenting demographics information in a database system
US20030167265A1 (en) 2001-06-07 2003-09-04 Corynen Guy Charles Computer method and user interface for decision analysis and for global system optimization
US20030182582A1 (en) 2002-03-19 2003-09-25 Park Jong Sou Network security simulation system
US20030220928A1 (en) 2002-05-21 2003-11-27 Patrick Durand Method for organizing and querying a genomic and proteomic databases
US20040034616A1 (en) 2002-04-26 2004-02-19 Andrew Witkowski Using relational structures to create and support a cube within a relational database system
US20040078105A1 (en) 2002-09-03 2004-04-22 Charles Moon System and method for workflow process management
US6778873B1 (en) 2002-07-31 2004-08-17 Advanced Micro Devices, Inc. Identifying a cause of a fault based on a process controller output
US6784902B1 (en) 1999-09-04 2004-08-31 National Instruments Corporation Method for configuration and parameterization of a graphical computer program for the operation of a data processing system
US20050010877A1 (en) 2003-07-11 2005-01-13 Arthur Udler System and method for dynamic generation of a graphical user interface
US20050022129A1 (en) 2003-06-17 2005-01-27 International Business Machines Corporation Method for managing tree representations in graphical user interfaces
US20050044525A1 (en) 2003-08-19 2005-02-24 Oracle International Corporation Techniques for partial loading of a configuration associated with a configuration model
US6993553B2 (en) 2000-12-19 2006-01-31 Sony Corporation Data providing system, data providing apparatus and method, data acquisition system and method, and program storage medium
US20060143534A1 (en) 2004-12-28 2006-06-29 Dall Elizabeth J Diagnostic memory dumping
US20060168205A1 (en) 2005-01-24 2006-07-27 Barron Gregory J Network analysis system and method
US20060173812A1 (en) 2004-09-30 2006-08-03 Yogesh Bahl System, software and method for examining a database in a forensic accounting environment
US20060247912A1 (en) 2005-04-27 2006-11-02 Microsoft Corporation Metric for evaluating systems that produce text
US20070016615A1 (en) 2004-03-31 2007-01-18 Fusionops Corporation Method and apparatus for developing composite applications
US20070106515A1 (en) 2005-11-09 2007-05-10 Sbc Knowledge Ventures, L.P. Automated interactive statistical call visualization using abstractions stack model framework
US20070112714A1 (en) 2002-02-01 2007-05-17 John Fairweather System and method for managing knowledge
US20070150581A1 (en) 2005-12-22 2007-06-28 American Express Travel Services, Co., Inc. a New York Corporation System and method for monitoring system performance levels across a network
US20070198312A1 (en) 2006-02-21 2007-08-23 Sugato Bagchi Data quality management using business process modeling
US20070214136A1 (en) 2006-03-13 2007-09-13 Microsoft Corporation Data mining diagramming
US20070288899A1 (en) 2006-06-13 2007-12-13 Microsoft Corporation Iterative static and dynamic software analysis
US20080040704A1 (en) 2006-08-14 2008-02-14 Payman Khodabandehloo Design tool and methodology for enterprise software applications
US20080059563A1 (en) 2003-10-30 2008-03-06 Lavastorm Technologies, Inc. Methods and Systems for Automated Data Processing
US7362718B2 (en) 2004-10-22 2008-04-22 Microsoft Corporation Maintaining membership within a federation infrastructure
US20080140688A1 (en) 2004-06-14 2008-06-12 Symphonyrpm, Inc. Decision object for associating a plurality of business plans
US20080150317A1 (en) 2006-12-20 2008-06-26 Richard Kilcrease Motorcycle trailer
US20080155440A1 (en) 2006-12-20 2008-06-26 Yahoo! Inc. Graphical user interface to manipulate syndication data feeds
US20080159317A1 (en) 2006-12-28 2008-07-03 Sap Ag Data organization and evaluation using a two-topology configuration
US20080183687A1 (en) 2007-01-31 2008-07-31 Salesforce.Com, Inc. Method and system for presenting a visual representation of the portion of the sets of data that a query is expected to return
US20080195626A1 (en) 2004-11-12 2008-08-14 Just Systems Corporation Data Processing Device,Document Processing Device,Data Relay Device,Data Processing Method ,and Data Relay Method
US20080209392A1 (en) 2007-02-26 2008-08-28 Able Steve L Systems and Methods for Definition and Execution of Batch Processing Services
US20080254430A1 (en) 2007-04-12 2008-10-16 Microsoft Corporation Parent guide to learning progress for use in a computerized learning environment
US20080262988A1 (en) 2007-04-20 2008-10-23 Mark Williams Vertical curve system for surface grading
US20080281801A1 (en) 2007-05-07 2008-11-13 Applied Technical Systems, Inc. Database system and related method
US20090018996A1 (en) 2007-01-26 2009-01-15 Herbert Dennis Hunt Cross-category view of a dataset using an analytic platform
US20090021767A1 (en) 2004-11-12 2009-01-22 Justsystems Corporation Document processing device
US20090064053A1 (en) 2007-08-31 2009-03-05 Fair Isaac Corporation Visualization of Decision Logic
US20090100086A1 (en) 2007-10-12 2009-04-16 Business Objects, S.A. Apparatus and method for visualizing data within a decomposition graph
US20090248698A1 (en) 2008-03-31 2009-10-01 Stephan Rehmann Managing Consistent Interfaces for Internal Service Request Business Objects Across Heterogeneous Systems
US20090276724A1 (en) 2008-04-07 2009-11-05 Rosenthal Philip J Interface Including Graphic Representation of Relationships Between Search Results
US20090319688A1 (en) 2008-06-24 2009-12-24 Microsoft Corporation Participating in cloud as totally stubby edge
US20100057618A1 (en) 2008-08-27 2010-03-04 Sean Andrew Spicer System, method, and software to manage financial securities via a 3-dimensional landscape
US7720779B1 (en) 2006-01-23 2010-05-18 Quantum Leap Research, Inc. Extensible bayesian network editor with inferencing capabilities
US20100156889A1 (en) 2008-12-18 2010-06-24 Microsoft Corporation Bi-directional update of a grid and associated visualizations
US7793160B1 (en) 2005-03-29 2010-09-07 Emc Corporation Systems and methods for tracing errors
US20100299327A1 (en) 2009-05-22 2010-11-25 International Business Machines Corporation Generating Structured Query Language/Extensible Markup Language (SQL/XML) Statements
US7991723B1 (en) 2007-07-16 2011-08-02 Sonicwall, Inc. Data pattern analysis using optimized deterministic finite automaton
US20110283242A1 (en) 2010-05-14 2011-11-17 Sap Ag Report or application screen searching
US20110302551A1 (en) 2010-06-02 2011-12-08 Hummel Jr David Martin System and method for analytic process design
US20110320384A1 (en) 2010-06-24 2011-12-29 Cherng Chang Stock market filters
US20120022707A1 (en) 2003-08-08 2012-01-26 Electric Power Group, Llc Wide-area, real-time monitoring and visualization system
US20120023302A1 (en) 2010-07-20 2012-01-26 Ibm Corporation Concurrent Atomic Operations with Page Migration in PCIe
US20120102396A1 (en) 2010-10-26 2012-04-26 Inetco Systems Limited Method and system for interactive visualization of hierarchical time series data
US20120151453A1 (en) 2009-06-10 2012-06-14 ITI Scotland Limited, Atrium Court Automated debugging system and method
US20120209886A1 (en) 2010-12-30 2012-08-16 Coral Networks, Inc. System and method for creating, deploying, integrating, and distributing
US20120226742A1 (en) 2011-03-03 2012-09-06 Citrix Systems Inc. Transparent User Interface Integration Between Local and Remote Computing Environments
US20120290950A1 (en) 2011-05-12 2012-11-15 Jeffrey A. Rapaport Social-topical adaptive networking (stan) system allowing for group based contextual transaction offers and acceptances and hot topic watchdogging
US20120330869A1 (en) 2011-06-25 2012-12-27 Jayson Theordore Durham Mental Model Elicitation Device (MMED) Methods and Apparatus
US20130042154A1 (en) 2011-08-12 2013-02-14 Microsoft Corporation Adaptive and Distributed Approach to Analyzing Program Behavior
US20130080197A1 (en) 2011-09-22 2013-03-28 David Kung Evaluating a trust value of a data report from a data processing tool
US8418181B1 (en) 2009-06-02 2013-04-09 Amazon Technologies, Inc. Managing program execution based on data storage location
US20130166568A1 (en) 2011-12-23 2013-06-27 Nou Data Corporation Scalable analysis platform for semi-structured data
US8479136B2 (en) 2011-05-03 2013-07-02 International Business Machines Corporation Decoupling capacitor insertion using hypergraph connectivity analysis
US20130212234A1 (en) 2012-02-14 2013-08-15 James P. Bartlett Providing configurable workflow capabilities
US20130283106A1 (en) 2012-04-23 2013-10-24 Edward Scott King Management of data in a supply chain transaction
US8626475B1 (en) 2009-12-29 2014-01-07 Comsol Ab System and method for accessing a multiphysics modeling system via a design system user interface
US20140043325A1 (en) 2012-08-10 2014-02-13 Microsoft Corporation Facetted browsing
US20140058775A1 (en) 2012-08-26 2014-02-27 Ole Siig Methods and systems for managing supply chain processes and intelligence
US8700682B2 (en) 2009-12-24 2014-04-15 Vertafore, Inc. Systems, methods and articles for template based generation of markup documents to access back office systems
US8806377B2 (en) 2009-09-01 2014-08-12 Oracle International Corporation Method and system for providing graphical user interface with contextual view
US8812752B1 (en) 2012-12-18 2014-08-19 Amazon Technologies, Inc. Connector interface for data pipeline
US8819592B2 (en) 2010-09-03 2014-08-26 Robert Lewis Jackson, JR. Sparse dynamic selection trees
US20140249999A1 (en) 2011-07-17 2014-09-04 Visa International Service Association Multiple Merchant Payment Processor Platform Apparatuses, Methods and Systems
US20140250153A1 (en) 2013-03-04 2014-09-04 Fisher-Rosemount Systems, Inc. Big data in process control systems
US8843959B2 (en) 2007-09-19 2014-09-23 Orlando McMaster Generating synchronized interactive link maps linking tracked video objects to other multimedia content in real-time
US8863029B2 (en) 2009-09-01 2014-10-14 Oracle International Corporation Method and system for providing graphical user interface having filtering capability
US20140365533A1 (en) 2011-12-23 2014-12-11 The Arizona Board Of Regents On Behalf Of The University Of Arizona Methods of micro-specialization in database management systems
US20150010143A1 (en) 2009-04-30 2015-01-08 HGST Netherlands B.V. Systems and methods for signature computation in a content locality based cache
US8976672B2 (en) 2006-10-03 2015-03-10 Cisco Technology, Inc. Efficiently decoupling reservation and data forwarding of data flows in a computer network
US20150081701A1 (en) 2013-09-16 2015-03-19 Metanautix, Inc. Systems and methods for data flow exploration
US20150106456A1 (en) 2013-10-10 2015-04-16 Jvl Ventures, Llc Systems, methods, and computer program products for managing communications
US20150149912A1 (en) 2013-11-22 2015-05-28 Raytheon Company Interactive multimedia process flow chart analysis
US20150178877A1 (en) 2013-10-18 2015-06-25 Palantir Technologies Inc. Overview user interface of emergency call data of a law enforcement agency
US20150200867A1 (en) 2014-01-15 2015-07-16 Cisco Technology, Inc. Task scheduling using virtual clusters
US20150278258A1 (en) 2014-03-31 2015-10-01 Matthias Kienzle Data cleansing tool with new cleansing tree
US20150317344A1 (en) 2009-06-25 2015-11-05 University Of Tennessee Research Foundation Method and apparatus for predicting object properties using similarity based information retrieval and modeling
US20150324437A1 (en) 2014-05-11 2015-11-12 Informatica Corporation Grid format data viewing and editing environment
US20150378869A1 (en) 2014-06-27 2015-12-31 Vmware, Inc. Measuring the logging quality of a computer program
US20150378863A1 (en) 2014-06-27 2015-12-31 Vmware, Inc. Enhancements to logging of a computer program
US20160062737A1 (en) 2014-09-02 2016-03-03 Ab Initio Technology Llc Specifying control and data connections in graph-based programs
US20160070451A1 (en) 2014-09-05 2016-03-10 Tableau Software, Inc. Graphical User Interface that Simplifies User Creation of Custom Calculations for Data Visualizations
US20160070430A1 (en) 2014-09-08 2016-03-10 Tableau Software Inc. Systems and Methods for Providing Drag and Drop Analytics in a Dynamic Data Visualization Interface
US20160086260A1 (en) 2014-09-19 2016-03-24 Amazon Technologies, Inc. Lifecycle transitions in log-coordinated data stores
US20160092476A1 (en) 2014-09-26 2016-03-31 Oracle International Corporation Declarative external data source importation, exportation, and metadata reflection utilizing http and hdfs protocols
US20160112460A1 (en) 2013-10-31 2016-04-21 Huawei Technologies Co., Ltd. Conflict detection and resolution methods and apparatuses
US20160110369A1 (en) 2014-10-16 2016-04-21 Palantir Technologies Inc. Schematic and database linking system
US9323503B1 (en) 2009-12-29 2016-04-26 Comsol Ab System and method for accessing settings in a multiphysics modeling system using a model tree
US20160117371A1 (en) 2014-10-23 2016-04-28 Microsoft Corporation Job authoring with data preview
US9335911B1 (en) 2014-12-29 2016-05-10 Palantir Technologies Inc. Interactive user interface for dynamic data analysis exploration and query processing
US20160179897A1 (en) 2014-12-18 2016-06-23 Salesforce.Com, Inc. Data extraction using object relationship templates
US20160260063A1 (en) 2015-03-03 2016-09-08 Adp, Llc Dynamic nodes for managing organization structure
US9465523B2 (en) 2013-06-27 2016-10-11 Sap Se Visual exploration of multidimensional data
US20160306908A1 (en) 2005-08-19 2016-10-20 Comsol Ab System and method for accessing settings in a multiphysics modeling system using a model tree
US9501585B1 (en) 2013-06-13 2016-11-22 DataRPM Corporation Methods and system for providing real-time business intelligence using search-based analytics engine
US20160364434A1 (en) 2015-06-12 2016-12-15 Ab Initio Technology Llc Data quality analysis
US20170005674A1 (en) 2015-07-02 2017-01-05 Apple Inc. Stopping Criteria for Turbo Decoder
US20170032026A1 (en) 2011-11-04 2017-02-02 BigML, Inc. Interactive visualization of big data sets and models including textual data
US20170039500A1 (en) 2012-08-26 2017-02-09 Thomson Reuters Global Resources Supply chain intelligence search engine
US20170069118A1 (en) 2014-09-08 2017-03-09 Tableau Software, Inc. Interactive Data Visualization User Interface with Multiple Interaction Profiles
US20170083585A1 (en) 2015-09-21 2017-03-23 Splunk Inc. Circular timeline displays of timestamped event data
US20170116396A1 (en) 2014-03-31 2017-04-27 Irdeto B.V. Optimizing and protecting software
US20170212944A1 (en) 2016-01-26 2017-07-27 Socrata, Inc. Automated computer visualization and interaction with big data
US9760240B2 (en) * 2014-10-09 2017-09-12 Splunk Inc. Graphical user interface for static and adaptive thresholds
US20170277664A1 (en) 2016-03-23 2017-09-28 Microsoft Technology Licensing, Llc Graphical data presented in code editor along with code
US20170286264A1 (en) 2016-03-29 2017-10-05 Infosys Limited System and method for data element tracing
US20170315516A1 (en) 2014-12-02 2017-11-02 Siemens Aktiengesellschaft Apparatus and Method for Monitoring A Device Having A Movable Part
US20170373932A1 (en) 2016-06-22 2017-12-28 Amazon Technologies, Inc. Configuration discovery service data visualization
US20170373992A1 (en) 2016-06-22 2017-12-28 Clickatell Corporation Digital interaction process automation
US20180024701A1 (en) 2016-07-21 2018-01-25 Palantir Technologies Inc. Cached database and synchronization system for providing dynamic linked panels in user interface
US20180024731A1 (en) 2016-07-21 2018-01-25 Palantir Technologies Inc. System for providing dynamic linked panels in user interface
US20180129374A1 (en) 2016-11-07 2018-05-10 Tableau Software, Inc. Generating and Applying Data Transformations in a Data Import Engine
US20180129719A1 (en) 2016-11-07 2018-05-10 Tableau Software, Inc. Optimizing Execution of Data Transformation Flows
US20180157579A1 (en) 2016-12-07 2018-06-07 Ab Initio Technology Llc Differencing of executable dataflow graphs
US20180165297A1 (en) 2016-12-09 2018-06-14 Salesforce.Com, Inc. Systems and methods for providing database updates for data visualization
US20180314764A1 (en) 2017-04-28 2018-11-01 Sisense Ltd. System and method for providing improved interfaces for data operations based on a connections graph
US10127250B2 (en) 2011-11-03 2018-11-13 Pervasive Software Ince. Data transformation system, graphical mapping tool and method for creating a schema map
US10127511B1 (en) 2017-09-22 2018-11-13 1Nteger, Llc Systems and methods for investigating and evaluating financial crime and sanctions-related risks
US20180349251A1 (en) 2017-06-06 2018-12-06 Sap Se Automated Root Cause Detection Using Data Flow Analysis
US20180367371A1 (en) 2017-06-16 2018-12-20 Cisco Technology, Inc. Handling controller and node failure scenarios during data collection
US20190004929A1 (en) 2017-06-28 2019-01-03 Intel Corporation Software condition evaluation apparatus and methods
US10204173B2 (en) 2003-07-11 2019-02-12 Ca, Inc. System and method for storing metrics in a database
US20190121807A1 (en) 2016-06-19 2019-04-25 Data.World, Inc. Computerized tools to develop and manage data-driven projects collaboratively via a networked computing platform and collaborative datasets
US10275545B2 (en) 2013-03-15 2019-04-30 Ventana Systems, Inc. Modeling and simulation
US20190138675A1 (en) 2009-12-29 2019-05-09 Comsol Ab System and method for accessing settings in a multiphysics modeling system using a model tree
US20190179927A1 (en) 2017-12-11 2019-06-13 Paypal, Inc. Enterprise data services cockpit
US10339681B2 (en) 2013-11-22 2019-07-02 Raytheon Company Interactive multimedia process flow chart builder
US10380140B2 (en) 2015-11-30 2019-08-13 Tableau Software, Inc. Systems and methods for implementing a virtual machine for interactive visual analysis
US20190258575A1 (en) 2018-02-22 2019-08-22 Ca, Inc. Adaptive caching using navigational graphs
US10394691B1 (en) 2017-10-05 2019-08-27 Tableau Software, Inc. Resolution of data flow errors using the lineage of detected error conditions
US20190294421A1 (en) 2018-03-21 2019-09-26 Dspace Digital Signal Processing And Control Engineering Gmbh Method and system for editing a block diagram model
US10466978B1 (en) 2016-11-30 2019-11-05 Composable Analytics, Inc. Intelligent assistant for automating recommendations for analytics programs
US10503784B1 (en) 2016-07-31 2019-12-10 Splunk Inc. Control interface for asset tree monitoring
US10515093B2 (en) 2015-11-30 2019-12-24 Tableau Software, Inc. Systems and methods for interactive visual analysis using a specialized virtual machine
US20200012656A1 (en) 2016-11-07 2020-01-09 Tableau Software, Inc. Correlated Incremental Loading of Multiple Data Sets for an Interactive Data Prep Application
US10733165B1 (en) 2015-07-06 2020-08-04 Workiva Inc. Distributed processing using a node hierarchy
US11354165B1 (en) * 2017-07-13 2022-06-07 Workday, Inc. Automated cluster execution support for diverse code sources
US11651003B2 (en) * 2019-09-27 2023-05-16 Tableau Software, LLC Interactive data visualization interface for data and graph models

Patent Citations (165)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4357673A (en) 1980-04-18 1982-11-02 Hewlett-Packard Company Apparatus for performing measurements and error analysis of the measurements
US4458323A (en) 1980-04-18 1984-07-03 Hewlett-Packard Company Method of performing measurements and error analysis of the measurements
US5339392A (en) 1989-07-27 1994-08-16 Risberg Jeffrey S Apparatus and method for creation of a user definable video displayed document showing changes in real time data
US5421008A (en) 1991-11-08 1995-05-30 International Business Machines Corporation System for interactive graphical construction of a data base query and storing of the query object links as an object
US5999192A (en) 1996-04-30 1999-12-07 Lucent Technologies Inc. Interactive data exploration apparatus and methods
US20020080174A1 (en) 1997-08-18 2002-06-27 National Instruments Corporation System and method for configuring an instrument to perform measurement functions utilizing conversion of graphical programs into hardware implementations
US20020055947A1 (en) 1997-08-18 2002-05-09 National Instruments Corporation System and method for deploying a graphical program on an image acquisition device
US6278452B1 (en) 1998-09-18 2001-08-21 Oracle Corporation Concise dynamic user interface for comparing hierarchically structured collections of objects
US20020157086A1 (en) 1999-02-04 2002-10-24 Lewis Brad R. Methods and systems for developing data flow programs
US6470344B1 (en) 1999-05-29 2002-10-22 Oracle Corporation Buffering a hierarchical index of multi-dimensional data
US6784902B1 (en) 1999-09-04 2004-08-31 National Instruments Corporation Method for configuration and parameterization of a graphical computer program for the operation of a data processing system
US20020070953A1 (en) 2000-05-04 2002-06-13 Barg Timothy A. Systems and methods for visualizing and analyzing conditioned data
US6993553B2 (en) 2000-12-19 2006-01-31 Sony Corporation Data providing system, data providing apparatus and method, data acquisition system and method, and program storage medium
US20030167265A1 (en) 2001-06-07 2003-09-04 Corynen Guy Charles Computer method and user interface for decision analysis and for global system optimization
US20030088546A1 (en) 2001-10-12 2003-05-08 Brown Douglas P. Collecting and/or presenting demographics information in a database system
US20070112714A1 (en) 2002-02-01 2007-05-17 John Fairweather System and method for managing knowledge
US20030182582A1 (en) 2002-03-19 2003-09-25 Park Jong Sou Network security simulation system
US20040034616A1 (en) 2002-04-26 2004-02-19 Andrew Witkowski Using relational structures to create and support a cube within a relational database system
US20030220928A1 (en) 2002-05-21 2003-11-27 Patrick Durand Method for organizing and querying a genomic and proteomic databases
US6778873B1 (en) 2002-07-31 2004-08-17 Advanced Micro Devices, Inc. Identifying a cause of a fault based on a process controller output
US20040078105A1 (en) 2002-09-03 2004-04-22 Charles Moon System and method for workflow process management
US20050022129A1 (en) 2003-06-17 2005-01-27 International Business Machines Corporation Method for managing tree representations in graphical user interfaces
US20050010877A1 (en) 2003-07-11 2005-01-13 Arthur Udler System and method for dynamic generation of a graphical user interface
US10204173B2 (en) 2003-07-11 2019-02-12 Ca, Inc. System and method for storing metrics in a database
US20120278015A1 (en) 2003-08-08 2012-11-01 Budhraja Vikram S Wide-area, real-time monitoring and visualization system
US20120022707A1 (en) 2003-08-08 2012-01-26 Electric Power Group, Llc Wide-area, real-time monitoring and visualization system
US20050044525A1 (en) 2003-08-19 2005-02-24 Oracle International Corporation Techniques for partial loading of a configuration associated with a configuration model
US20080059563A1 (en) 2003-10-30 2008-03-06 Lavastorm Technologies, Inc. Methods and Systems for Automated Data Processing
US20070016615A1 (en) 2004-03-31 2007-01-18 Fusionops Corporation Method and apparatus for developing composite applications
US20080140688A1 (en) 2004-06-14 2008-06-12 Symphonyrpm, Inc. Decision object for associating a plurality of business plans
US20060173812A1 (en) 2004-09-30 2006-08-03 Yogesh Bahl System, software and method for examining a database in a forensic accounting environment
US7362718B2 (en) 2004-10-22 2008-04-22 Microsoft Corporation Maintaining membership within a federation infrastructure
US20080195626A1 (en) 2004-11-12 2008-08-14 Just Systems Corporation Data Processing Device,Document Processing Device,Data Relay Device,Data Processing Method ,and Data Relay Method
US20090021767A1 (en) 2004-11-12 2009-01-22 Justsystems Corporation Document processing device
US20060143534A1 (en) 2004-12-28 2006-06-29 Dall Elizabeth J Diagnostic memory dumping
US20060168205A1 (en) 2005-01-24 2006-07-27 Barron Gregory J Network analysis system and method
US7793160B1 (en) 2005-03-29 2010-09-07 Emc Corporation Systems and methods for tracing errors
US20060247912A1 (en) 2005-04-27 2006-11-02 Microsoft Corporation Metric for evaluating systems that produce text
US20160306908A1 (en) 2005-08-19 2016-10-20 Comsol Ab System and method for accessing settings in a multiphysics modeling system using a model tree
US20070106515A1 (en) 2005-11-09 2007-05-10 Sbc Knowledge Ventures, L.P. Automated interactive statistical call visualization using abstractions stack model framework
US20070150581A1 (en) 2005-12-22 2007-06-28 American Express Travel Services, Co., Inc. a New York Corporation System and method for monitoring system performance levels across a network
US7720779B1 (en) 2006-01-23 2010-05-18 Quantum Leap Research, Inc. Extensible bayesian network editor with inferencing capabilities
US20070198312A1 (en) 2006-02-21 2007-08-23 Sugato Bagchi Data quality management using business process modeling
US20070214136A1 (en) 2006-03-13 2007-09-13 Microsoft Corporation Data mining diagramming
US20070288899A1 (en) 2006-06-13 2007-12-13 Microsoft Corporation Iterative static and dynamic software analysis
US20080040704A1 (en) 2006-08-14 2008-02-14 Payman Khodabandehloo Design tool and methodology for enterprise software applications
US8976672B2 (en) 2006-10-03 2015-03-10 Cisco Technology, Inc. Efficiently decoupling reservation and data forwarding of data flows in a computer network
US20080155440A1 (en) 2006-12-20 2008-06-26 Yahoo! Inc. Graphical user interface to manipulate syndication data feeds
US20080150317A1 (en) 2006-12-20 2008-06-26 Richard Kilcrease Motorcycle trailer
US20080159317A1 (en) 2006-12-28 2008-07-03 Sap Ag Data organization and evaluation using a two-topology configuration
US20090018996A1 (en) 2007-01-26 2009-01-15 Herbert Dennis Hunt Cross-category view of a dataset using an analytic platform
US20080183687A1 (en) 2007-01-31 2008-07-31 Salesforce.Com, Inc. Method and system for presenting a visual representation of the portion of the sets of data that a query is expected to return
US20080209392A1 (en) 2007-02-26 2008-08-28 Able Steve L Systems and Methods for Definition and Execution of Batch Processing Services
US20080254430A1 (en) 2007-04-12 2008-10-16 Microsoft Corporation Parent guide to learning progress for use in a computerized learning environment
US20080262988A1 (en) 2007-04-20 2008-10-23 Mark Williams Vertical curve system for surface grading
US20080281801A1 (en) 2007-05-07 2008-11-13 Applied Technical Systems, Inc. Database system and related method
US7991723B1 (en) 2007-07-16 2011-08-02 Sonicwall, Inc. Data pattern analysis using optimized deterministic finite automaton
US20090064053A1 (en) 2007-08-31 2009-03-05 Fair Isaac Corporation Visualization of Decision Logic
US8843959B2 (en) 2007-09-19 2014-09-23 Orlando McMaster Generating synchronized interactive link maps linking tracked video objects to other multimedia content in real-time
US20090100086A1 (en) 2007-10-12 2009-04-16 Business Objects, S.A. Apparatus and method for visualizing data within a decomposition graph
US20090248698A1 (en) 2008-03-31 2009-10-01 Stephan Rehmann Managing Consistent Interfaces for Internal Service Request Business Objects Across Heterogeneous Systems
US20090276724A1 (en) 2008-04-07 2009-11-05 Rosenthal Philip J Interface Including Graphic Representation of Relationships Between Search Results
US20090319688A1 (en) 2008-06-24 2009-12-24 Microsoft Corporation Participating in cloud as totally stubby edge
US20100057618A1 (en) 2008-08-27 2010-03-04 Sean Andrew Spicer System, method, and software to manage financial securities via a 3-dimensional landscape
US20100156889A1 (en) 2008-12-18 2010-06-24 Microsoft Corporation Bi-directional update of a grid and associated visualizations
US20150010143A1 (en) 2009-04-30 2015-01-08 HGST Netherlands B.V. Systems and methods for signature computation in a content locality based cache
US20100299327A1 (en) 2009-05-22 2010-11-25 International Business Machines Corporation Generating Structured Query Language/Extensible Markup Language (SQL/XML) Statements
US8418181B1 (en) 2009-06-02 2013-04-09 Amazon Technologies, Inc. Managing program execution based on data storage location
US20120151453A1 (en) 2009-06-10 2012-06-14 ITI Scotland Limited, Atrium Court Automated debugging system and method
US20150317344A1 (en) 2009-06-25 2015-11-05 University Of Tennessee Research Foundation Method and apparatus for predicting object properties using similarity based information retrieval and modeling
US8863029B2 (en) 2009-09-01 2014-10-14 Oracle International Corporation Method and system for providing graphical user interface having filtering capability
US8806377B2 (en) 2009-09-01 2014-08-12 Oracle International Corporation Method and system for providing graphical user interface with contextual view
US8700682B2 (en) 2009-12-24 2014-04-15 Vertafore, Inc. Systems, methods and articles for template based generation of markup documents to access back office systems
US8626475B1 (en) 2009-12-29 2014-01-07 Comsol Ab System and method for accessing a multiphysics modeling system via a design system user interface
US9323503B1 (en) 2009-12-29 2016-04-26 Comsol Ab System and method for accessing settings in a multiphysics modeling system using a model tree
US20190138675A1 (en) 2009-12-29 2019-05-09 Comsol Ab System and method for accessing settings in a multiphysics modeling system using a model tree
US20110283242A1 (en) 2010-05-14 2011-11-17 Sap Ag Report or application screen searching
US20110302551A1 (en) 2010-06-02 2011-12-08 Hummel Jr David Martin System and method for analytic process design
US20110320384A1 (en) 2010-06-24 2011-12-29 Cherng Chang Stock market filters
US20120023302A1 (en) 2010-07-20 2012-01-26 Ibm Corporation Concurrent Atomic Operations with Page Migration in PCIe
US8819592B2 (en) 2010-09-03 2014-08-26 Robert Lewis Jackson, JR. Sparse dynamic selection trees
US20120102396A1 (en) 2010-10-26 2012-04-26 Inetco Systems Limited Method and system for interactive visualization of hierarchical time series data
US20120209886A1 (en) 2010-12-30 2012-08-16 Coral Networks, Inc. System and method for creating, deploying, integrating, and distributing
US20120226742A1 (en) 2011-03-03 2012-09-06 Citrix Systems Inc. Transparent User Interface Integration Between Local and Remote Computing Environments
US8479136B2 (en) 2011-05-03 2013-07-02 International Business Machines Corporation Decoupling capacitor insertion using hypergraph connectivity analysis
US20120290950A1 (en) 2011-05-12 2012-11-15 Jeffrey A. Rapaport Social-topical adaptive networking (stan) system allowing for group based contextual transaction offers and acceptances and hot topic watchdogging
US20120330869A1 (en) 2011-06-25 2012-12-27 Jayson Theordore Durham Mental Model Elicitation Device (MMED) Methods and Apparatus
US20140249999A1 (en) 2011-07-17 2014-09-04 Visa International Service Association Multiple Merchant Payment Processor Platform Apparatuses, Methods and Systems
US20130042154A1 (en) 2011-08-12 2013-02-14 Microsoft Corporation Adaptive and Distributed Approach to Analyzing Program Behavior
US20130080197A1 (en) 2011-09-22 2013-03-28 David Kung Evaluating a trust value of a data report from a data processing tool
US10127250B2 (en) 2011-11-03 2018-11-13 Pervasive Software Ince. Data transformation system, graphical mapping tool and method for creating a schema map
US20170032026A1 (en) 2011-11-04 2017-02-02 BigML, Inc. Interactive visualization of big data sets and models including textual data
US20140365533A1 (en) 2011-12-23 2014-12-11 The Arizona Board Of Regents On Behalf Of The University Of Arizona Methods of micro-specialization in database management systems
US20130166568A1 (en) 2011-12-23 2013-06-27 Nou Data Corporation Scalable analysis platform for semi-structured data
US20130212234A1 (en) 2012-02-14 2013-08-15 James P. Bartlett Providing configurable workflow capabilities
US20130283106A1 (en) 2012-04-23 2013-10-24 Edward Scott King Management of data in a supply chain transaction
US20140043325A1 (en) 2012-08-10 2014-02-13 Microsoft Corporation Facetted browsing
US20170039500A1 (en) 2012-08-26 2017-02-09 Thomson Reuters Global Resources Supply chain intelligence search engine
US20140058775A1 (en) 2012-08-26 2014-02-27 Ole Siig Methods and systems for managing supply chain processes and intelligence
US8812752B1 (en) 2012-12-18 2014-08-19 Amazon Technologies, Inc. Connector interface for data pipeline
US20140250153A1 (en) 2013-03-04 2014-09-04 Fisher-Rosemount Systems, Inc. Big data in process control systems
US10275545B2 (en) 2013-03-15 2019-04-30 Ventana Systems, Inc. Modeling and simulation
US9501585B1 (en) 2013-06-13 2016-11-22 DataRPM Corporation Methods and system for providing real-time business intelligence using search-based analytics engine
US9465523B2 (en) 2013-06-27 2016-10-11 Sap Se Visual exploration of multidimensional data
US20150081701A1 (en) 2013-09-16 2015-03-19 Metanautix, Inc. Systems and methods for data flow exploration
US20150106456A1 (en) 2013-10-10 2015-04-16 Jvl Ventures, Llc Systems, methods, and computer program products for managing communications
US20150178877A1 (en) 2013-10-18 2015-06-25 Palantir Technologies Inc. Overview user interface of emergency call data of a law enforcement agency
US20160112460A1 (en) 2013-10-31 2016-04-21 Huawei Technologies Co., Ltd. Conflict detection and resolution methods and apparatuses
US20150149912A1 (en) 2013-11-22 2015-05-28 Raytheon Company Interactive multimedia process flow chart analysis
US10339681B2 (en) 2013-11-22 2019-07-02 Raytheon Company Interactive multimedia process flow chart builder
US20150200867A1 (en) 2014-01-15 2015-07-16 Cisco Technology, Inc. Task scheduling using virtual clusters
US20170116396A1 (en) 2014-03-31 2017-04-27 Irdeto B.V. Optimizing and protecting software
US20150278258A1 (en) 2014-03-31 2015-10-01 Matthias Kienzle Data cleansing tool with new cleansing tree
US20150324437A1 (en) 2014-05-11 2015-11-12 Informatica Corporation Grid format data viewing and editing environment
US20150378863A1 (en) 2014-06-27 2015-12-31 Vmware, Inc. Enhancements to logging of a computer program
US20150378869A1 (en) 2014-06-27 2015-12-31 Vmware, Inc. Measuring the logging quality of a computer program
US20160062737A1 (en) 2014-09-02 2016-03-03 Ab Initio Technology Llc Specifying control and data connections in graph-based programs
US20160070451A1 (en) 2014-09-05 2016-03-10 Tableau Software, Inc. Graphical User Interface that Simplifies User Creation of Custom Calculations for Data Visualizations
US20170069118A1 (en) 2014-09-08 2017-03-09 Tableau Software, Inc. Interactive Data Visualization User Interface with Multiple Interaction Profiles
US20160070430A1 (en) 2014-09-08 2016-03-10 Tableau Software Inc. Systems and Methods for Providing Drag and Drop Analytics in a Dynamic Data Visualization Interface
US20160086260A1 (en) 2014-09-19 2016-03-24 Amazon Technologies, Inc. Lifecycle transitions in log-coordinated data stores
US20160092476A1 (en) 2014-09-26 2016-03-31 Oracle International Corporation Declarative external data source importation, exportation, and metadata reflection utilizing http and hdfs protocols
US9760240B2 (en) * 2014-10-09 2017-09-12 Splunk Inc. Graphical user interface for static and adaptive thresholds
US20160110369A1 (en) 2014-10-16 2016-04-21 Palantir Technologies Inc. Schematic and database linking system
US20160117371A1 (en) 2014-10-23 2016-04-28 Microsoft Corporation Job authoring with data preview
US20170315516A1 (en) 2014-12-02 2017-11-02 Siemens Aktiengesellschaft Apparatus and Method for Monitoring A Device Having A Movable Part
US20160179897A1 (en) 2014-12-18 2016-06-23 Salesforce.Com, Inc. Data extraction using object relationship templates
US9335911B1 (en) 2014-12-29 2016-05-10 Palantir Technologies Inc. Interactive user interface for dynamic data analysis exploration and query processing
US20160260063A1 (en) 2015-03-03 2016-09-08 Adp, Llc Dynamic nodes for managing organization structure
US20160364434A1 (en) 2015-06-12 2016-12-15 Ab Initio Technology Llc Data quality analysis
US20170005674A1 (en) 2015-07-02 2017-01-05 Apple Inc. Stopping Criteria for Turbo Decoder
US10733165B1 (en) 2015-07-06 2020-08-04 Workiva Inc. Distributed processing using a node hierarchy
US20170083585A1 (en) 2015-09-21 2017-03-23 Splunk Inc. Circular timeline displays of timestamped event data
US10380140B2 (en) 2015-11-30 2019-08-13 Tableau Software, Inc. Systems and methods for implementing a virtual machine for interactive visual analysis
US10515093B2 (en) 2015-11-30 2019-12-24 Tableau Software, Inc. Systems and methods for interactive visual analysis using a specialized virtual machine
US20170212944A1 (en) 2016-01-26 2017-07-27 Socrata, Inc. Automated computer visualization and interaction with big data
US20170277664A1 (en) 2016-03-23 2017-09-28 Microsoft Technology Licensing, Llc Graphical data presented in code editor along with code
US20170286264A1 (en) 2016-03-29 2017-10-05 Infosys Limited System and method for data element tracing
US20190121807A1 (en) 2016-06-19 2019-04-25 Data.World, Inc. Computerized tools to develop and manage data-driven projects collaboratively via a networked computing platform and collaborative datasets
US20170373932A1 (en) 2016-06-22 2017-12-28 Amazon Technologies, Inc. Configuration discovery service data visualization
US20170373992A1 (en) 2016-06-22 2017-12-28 Clickatell Corporation Digital interaction process automation
US20180024701A1 (en) 2016-07-21 2018-01-25 Palantir Technologies Inc. Cached database and synchronization system for providing dynamic linked panels in user interface
US20180024731A1 (en) 2016-07-21 2018-01-25 Palantir Technologies Inc. System for providing dynamic linked panels in user interface
US10503784B1 (en) 2016-07-31 2019-12-10 Splunk Inc. Control interface for asset tree monitoring
US20180129720A1 (en) 2016-11-07 2018-05-10 Tableau Software, Inc. User Interface for Graphically Refactoring Data Flows
US20180129719A1 (en) 2016-11-07 2018-05-10 Tableau Software, Inc. Optimizing Execution of Data Transformation Flows
US10242079B2 (en) 2016-11-07 2019-03-26 Tableau Software, Inc. Optimizing execution of data transformation flows
US10528587B2 (en) 2016-11-07 2020-01-07 Tableau Software, Inc. User interface for graphically refactoring data flows
US20180129374A1 (en) 2016-11-07 2018-05-10 Tableau Software, Inc. Generating and Applying Data Transformations in a Data Import Engine
US20200012656A1 (en) 2016-11-07 2020-01-09 Tableau Software, Inc. Correlated Incremental Loading of Multiple Data Sets for an Interactive Data Prep Application
US10885057B2 (en) 2016-11-07 2021-01-05 Tableau Software, Inc. Correlated incremental loading of multiple data sets for an interactive data prep application
US10466978B1 (en) 2016-11-30 2019-11-05 Composable Analytics, Inc. Intelligent assistant for automating recommendations for analytics programs
US20180157579A1 (en) 2016-12-07 2018-06-07 Ab Initio Technology Llc Differencing of executable dataflow graphs
US20180165297A1 (en) 2016-12-09 2018-06-14 Salesforce.Com, Inc. Systems and methods for providing database updates for data visualization
US20180314764A1 (en) 2017-04-28 2018-11-01 Sisense Ltd. System and method for providing improved interfaces for data operations based on a connections graph
US20180349251A1 (en) 2017-06-06 2018-12-06 Sap Se Automated Root Cause Detection Using Data Flow Analysis
US20180367371A1 (en) 2017-06-16 2018-12-20 Cisco Technology, Inc. Handling controller and node failure scenarios during data collection
US20190004929A1 (en) 2017-06-28 2019-01-03 Intel Corporation Software condition evaluation apparatus and methods
US11354165B1 (en) * 2017-07-13 2022-06-07 Workday, Inc. Automated cluster execution support for diverse code sources
US10127511B1 (en) 2017-09-22 2018-11-13 1Nteger, Llc Systems and methods for investigating and evaluating financial crime and sanctions-related risks
US10394691B1 (en) 2017-10-05 2019-08-27 Tableau Software, Inc. Resolution of data flow errors using the lineage of detected error conditions
US20190179927A1 (en) 2017-12-11 2019-06-13 Paypal, Inc. Enterprise data services cockpit
US20190258575A1 (en) 2018-02-22 2019-08-22 Ca, Inc. Adaptive caching using navigational graphs
US20190294421A1 (en) 2018-03-21 2019-09-26 Dspace Digital Signal Processing And Control Engineering Gmbh Method and system for editing a block diagram model
US11651003B2 (en) * 2019-09-27 2023-05-16 Tableau Software, LLC Interactive data visualization interface for data and graph models

Non-Patent Citations (50)

* Cited by examiner, † Cited by third party
Title
Anand Notice of Allowance, U.S. Appl. No. 17/325,124, dated May 4, 2022, 12 pgs.
Anand Notice of Allowance, U.S. Appl. No. 17/947,027, dated Oct. 10, 2023, 10 pgs.
Anand, Notice of Allowance, U.S. Appl. No. 16/167,313, dated Mar. 2, 2020, 9 pgs.
Anand, Notice of Allowance, U.S. Appl. No. 16/908,700, dated Mar. 11, 2021, 10 pgs.
Anand, Preinterview First Office Action, U.S. Appl. No. 16/167,313, dated Jan. 24, 2020, 6 pgs.
Anonymous, "Cursor (databases) Wikipidia, the free enciclopedia," Dec. 2, 2012, XP055222764, Retrieved from the internet: URL:https://en.wikipedia,org/w/index.ph?title-Cursor (databases)&oldid=526008371, 7 pgs.
Bae, J., Understanding Indirect Casual Relationships in Node-Link Graphs, Eurographics Conference on Visualization (Euro Vis) Jun. 2017, vol. 36, No. 3, 12 pgs.
Cole, Notice of Allowance, U.S. Appl. No. 15/726,294, dated May 15, 2019, 14 pgs.
Cole, Office-Action, U.S. Appl. No. 15/726,294, dated Nov. 9, 2018, 40 pgs.
Disclosed Anonymously, ip.com Method to enter data while filter applied, Dec. 6, 2011, (YearL 2011), 7 pgs.
Ghani, S., Perception of Animated Node-Link Diagrams Graphs, Eurographics Conference on Visualization, (Euro Vis) Jun. 2012, vol. 31, No. 3, 11 pgs.
Ishio et al., "A Lightweight Visualization of Interprocedural Data-Flow Paths for Source Code Reading," [Online], 2012, pp. 37-46, retrieved from internet on May 7, 2019, <https://ieeexplore.org/stamp.jsp?tp-&arnumber-6240506> (Year: 2012).
Kabbaj et al., "Towards an Active Help on Detecting Data Flow Errors in Business Process Models," [Online}, 2015, pp. 16-25, [retrieved from internet on Jul. 11, 2020]<https://www.researchgate.net/profile/Mohammed_Isaam_Kabbaj/publication/263966796_Toward_an_active_help_on_detecting_data_flow_errors>(Year:2015), 11 pgs.
Kim, Final Office Action, U.S. Appl. No. 15/345,391, dated Jun. 6, 2022, 20 pgs.
Kim, Final Office Action, U.S. Appl. No. 15/345,391, dated Sep. 17, 2020, 16 pgs.
Kim, Final Office Action, U.S. Appl. No. 16/937,524, dated Aug. 23, 2022, 22 pgs.
Kim, Final Office Action—U.S. Appl. No. 15/701,392, dated Sep. 21, 2020, 18 pgs.
Kim, First Action Interview Office Action, U.S. Appl. No. 16/937,524, dated Mar. 10, 2022, 6 pgs.
Kim, Notice of Allowance U.S. Appl. No. 15/345,391, dated Aug. 25, 2023, 8 pgs.
Kim, Notice of Allowance, U.S. Appl. No. 15/701,381, dated Nov. 9, 2018, 6 pgs.
Kim, Notice of Allowance, U.S. Appl. No. 15/701,392, dated Apr. 20, 2021, 9 pgs.
Kim, Notice of Allowance, U.S. Appl. No. 15/705,174, dated Sep. 24, 2019, 10 pgs.
Kim, Notice of Allowance, U.S. Appl. No. 16/138,705, dated Aug. 7, 2020, 9 pgs.
Kim, Notice of Allowance, U.S. Appl. No. 16/153,615, dated Jul. 14, 2020, 10 pgs.
Kim, Notice of Allowance, U.S. Appl. No. 16/285,084, dated Apr. 6, 2020, 9 pgs.
Kim, Notice of Allowance, U.S. Appl. No. 16/537,444, dated Jul. 22, 2020, 13 pgs.
Kim, Office Action, U.S. Appl. No. 15/345,391, dated Feb. 13, 2020, 16 pgs.
Kim, Office Action, U.S. Appl. No. 15/345,391, dated Jun. 28, 2019, 10 pgs.
Kim, Office Action, U.S. Appl. No. 15/345,391, dated Jun. 8, 2021, 14 pgs.
Kim, Office Action, U.S. Appl. No. 16/937,524, dated Apr. 10, 2023, 26 pgs.
Kim, Pre-Interview First Office Action, U.S. Appl. No. 16/937,524, dated Jan. 6, 2022, 6 pgs.
Kim, Pre-Interview First Office Action—U.S. Appl. No. 15/701,392, dated Mar. 9, 2020, 5 pgs.
Logothetis et al., "Scalable Lineage Capture for Debugging DISC Analytics," [Online], 2013, pp. 1-15, retrieved from internet on May 7, 2019, <http://delivery.acm.org/10.1145/250000/252369/a17-logothetis.pdf> (Year:2013).
Lovat et al., "On Quantitative Dynamic Data Flow Tracking," [Online], 2014, pp. 211-222, [retrieved from internet on Jul. 11, 2020, <https://dl,acm/doi/pdf/10.11145/2557547.2557551> (Year: 2014), 12 pgs.
Meda et al., "On Detecting Data Flow Errors in Workflows," [Online] 2010, pp. 4:1-4:31, [retrieved from internet on Jul. 11, 2020], <https://dl.acm.org/doi/pdf/10.1145/1805286.1805290> (Year: 2020), 31 pgs.
Moser et al., "Advanced Verification of Distributed WS-BPEL Business Processes Incorporating CSSA-based Data Flow Analysis," [Online], 2007, pp. 1-8, [retrieved from internet on Jul. 11, 2020], <https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4278643> (Year: 2007), 8 pgs.
Moss, First Action Interview Office Action, U.S. Appl. No. 16/228,680, dated Aug. 26, 2021, 4 pgs.
Moss, Notice of Allowance, U.S. Appl. No. 16/228,680, dated Oct. 1, 2021, 10 pgs.
Moss, Notice of Allowance, U.S. Appl. No. 17/670,407, dated Dec. 28, 2023, 12 pgs.
Moss, Office Action, U.S. Appl. No. 17/670,407, dated Aug. 31, 2023, 24 pgs.
Moss, Pre-Interview First Office Action, U.S. Appl. No. 16/228,680, dated Jun. 8, 2021, 5 pgs.
Pugh, Notice of Allowance, U.S. Appl. No. 16/155,818, dated Oct. 1, 2020, 9 pgs.
Pugh, Notice of Allowance, U.S. Appl. No. 17/142,138, dated Aug. 5, 2021, 9 pgs.
Tableau Software, Inc., Communication Pursuant Rules 161(1) and 162, EP17801216.7, dated Jun. 17, 2019, 3 pgs.
Tableau Software, Inc., Communication Pursuant to Article 94(3), EP17801216.7, dated Apr. 3, 2020, 6 pgs.
Tableau Software, Inc., International Search Report and Written Opinion, PCT/US2017/060232, dated Jan. 18, 2018, 10 pgs.
Tableau Software, Inc., International Search Report and Written Opinion, PCT/US2019/053935, dated Dec. 18, 2019, 13 pgs.
Tibco, "Tibco ActiveMatrix BusinessWorks™ Process Design Software Release 5.13," Aug. 31, 2015, retrieved from the Internet: URL:https://docs.tibco.com/pub/activematrix_businessworks/5.13.0/doc/pdf/tib_bw_process_design_guide.pdf, 107 pgs.
Wildenradt, Notice of Allowance, U.S. Appl. No. 16/681,753, dated May 6, 2021, 10 pgs.
Yip et al., "Improving Application Security with Data Flow Assertions," [Online], 2009, pp. 1-18, retrieved from internet on May 7, 2019, <http://www.sigops.org/conferences/sosp/2009/papers/yip-sosp09.pdf> (Year:2009).

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